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Fix: Improve keyword extraction prompt for robust JSON output.

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*   Emphasize strict JSON output in key extration prompt
*   Clean up prompt examples in key extration prompt
*   Log raw LLM response on JSON error
This commit is contained in:
yangdx 2025-07-27 21:10:47 +08:00
parent 3f5ade47cd
commit f2d051eea5
2 changed files with 13 additions and 9 deletions
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1
lightrag/operate.py
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@ -1852,6 +1852,7 @@ async def extract_keywords_only(
keywords_data = json.loads(match.group(0)) keywords_data = json.loads(match.group(0))
except json.JSONDecodeError as e: except json.JSONDecodeError as e:
logger.error(f"JSON parsing error: {e}") logger.error(f"JSON parsing error: {e}")
logger.error(f"LLM respond: {result}")
return [], [] return [], []
hl_keywords = keywords_data.get("high_level_keywords", []) hl_keywords = keywords_data.get("high_level_keywords", [])

21
lightrag/prompt.py
View File

@ -251,7 +251,7 @@ Given the query and conversation history, list both high-level and low-level key
###################### ######################
{examples} {examples}
############################# ######################
---Real Data--- ---Real Data---
###################### ######################
Conversation History: Conversation History:
@ -259,42 +259,45 @@ Conversation History:
Current Query: {query} Current Query: {query}
###################### ######################
The `Output` should be human text, not unicode characters. Keep the same language as `Query`. The `Output` should be in JSON format, with no other text before and after the JSON. Use the same language as `Current Query`.
Output:
Output:
""" """
PROMPTS["keywords_extraction_examples"] = [ PROMPTS["keywords_extraction_examples"] = [
"""Example 1: """Example 1:
Query: "How does international trade influence global economic stability?" Query: "How does international trade influence global economic stability?"
################
Output: Output:
{ {
"high_level_keywords": ["International trade", "Global economic stability", "Economic impact"], "high_level_keywords": ["International trade", "Global economic stability", "Economic impact"],
"low_level_keywords": ["Trade agreements", "Tariffs", "Currency exchange", "Imports", "Exports"] "low_level_keywords": ["Trade agreements", "Tariffs", "Currency exchange", "Imports", "Exports"]
} }
#############################""",
""",
"""Example 2: """Example 2:
Query: "What are the environmental consequences of deforestation on biodiversity?" Query: "What are the environmental consequences of deforestation on biodiversity?"
################
Output: Output:
{ {
"high_level_keywords": ["Environmental consequences", "Deforestation", "Biodiversity loss"], "high_level_keywords": ["Environmental consequences", "Deforestation", "Biodiversity loss"],
"low_level_keywords": ["Species extinction", "Habitat destruction", "Carbon emissions", "Rainforest", "Ecosystem"] "low_level_keywords": ["Species extinction", "Habitat destruction", "Carbon emissions", "Rainforest", "Ecosystem"]
} }
#############################""",
""",
"""Example 3: """Example 3:
Query: "What is the role of education in reducing poverty?" Query: "What is the role of education in reducing poverty?"
################
Output: Output:
{ {
"high_level_keywords": ["Education", "Poverty reduction", "Socioeconomic development"], "high_level_keywords": ["Education", "Poverty reduction", "Socioeconomic development"],
"low_level_keywords": ["School access", "Literacy rates", "Job training", "Income inequality"] "low_level_keywords": ["School access", "Literacy rates", "Job training", "Income inequality"]
} }
#############################""",
""",
] ]
PROMPTS["naive_rag_response"] = """---Role--- PROMPTS["naive_rag_response"] = """---Role---